RedisAI 1.0.0 (May 2020)

Supported Backends:

  • TensorFlow Lite 2.0
  • TensorFlow 1.15.0
  • PyTorch 1.5
  • ONXXRuntime 1.2.0

New Features:

  • #241, #270 auto-batching support. Requests from multiple clients can be automatically and transparently batched in a single request for increased CPU/GPU efficiency during serving.
  • #322 Add AI.DAGRUN. With the new AI.DAGRUN (DAG as in direct acycilc graph) command we support the prescription of combinations of other AI.* commands in a single execution pass, where intermediate keys are never materialised to Redis.
  • #334 Add AI.DAGRUN_RO command, a read-only variant of AI.DAGRUN
  • #338 AI.MODELSET Added the possibility to provide a model in chunks.
  • #332 Standardized GET methods (TENSORGET,MODELGET,SCRIPTGET) replies (breaking change for clients)
  • #331 Cache model blobs for faster serialization and thread-safety.

Minor Enhancements:

  • #289 Memory access and leak fixes.
  • #319 Documentation improvements.

Build Enhancements:

  • #299 Coverage info.
  • #273 Enable running valgrind/callgrind on test platform
  • #277, #296 tests extension and refactoring per backend.